Field of the Invention
The present invention relates to an image processing system for processing a tomographic image of an object.
Description of the Related Art
To diagnose lifestyle related diseases and other various diseases, which may lead to blindness, in their early stages, inspections are conventionally performed based on captured images of eye portions (i.e., objects). For example, a tomographic image acquiring apparatus using an Optical Coherence Tomography (hereinafter, referred to as “OCT”) can be used to observe a three-dimensional state of an internal retinal layer of an eye portion. Therefore, the tomographic image acquiring apparatus is expected to be a prospective diagnosis apparatus that can accurately diagnose various diseases.
In a cross-sectional layer image (i.e., a tomographic image) of an eye portion obtained using the OCT, the stage of a disease (e.g., glaucoma, age-related macular degeneration, and macular edema) and the degree of recovery from the disease after treatment can be quantitatively diagnosed by measuring the thickness of each layer (e.g., a nerve fiber layer) that constitutes the retina in the eye portion or the thickness of the entire retinal layer.
Conventionally, to measure the thickness of each layer, it was necessary for a physician or an engineer to manually designate a boundary of each layer of the retina on a two-dimensional tomographic image (i.e., a B-scan image), which can be obtained by clipping a target cross section from a three-dimensionally captured tomographic image. Further, to obtain a three-dimensional distribution with respect to the thickness of each layer, it was necessary to presume a three-dimensional tomographic image as an assembly of two-dimensional tomographic images and designate a boundary of a target layer on each two-dimensional tomographic image.
However, the work for manually designating the boundary of the target layer is not easy for an operator (e.g., a physician or an engineer). Further, the work for manually designating the boundary of the target layer tends to generate a dispersion that results from differences of individual operators as well as differences in work date and time. Therefore, performing quantification at an expected accuracy level was difficult. As discussed in Japanese Patent Application Laid-Open No. 2008-73099 and Japanese Patent Application Laid-Open No. 2007-325831, for the purpose of reducing the operator's burden and eliminating the dispersion in the work, there is a conventional technique for causing a computer to detect a boundary of each layer of the retina from a tomographic image and measuring the thickness of each layer.
Further, the age-related macular degeneration or a similar disease is characteristic in that the shape of a retinal pigment epithelium changes into a wavy shape according to the condition of a disease. Therefore, it is effective to quantify the degree of its deformation to identify the condition of the disease.
FIGS. 20A to 20C are schematic views illustrating examples of the layer structure of a general retina. FIG. 20A illustrates an example of a retinal layer structure of a normal eye. FIG. 20B illustrates an example of a retinal layer structure that has changed due to the age-related macular degeneration. A retinal pigment epithelium 1400a of the normal eye illustrated in FIG. 20A includes a smooth curve that represents a boundary structure. On the other hand, a retinal pigment epithelium 1400b having been modified by the age-related macular degeneration illustrated in FIG. 20B has a portion whose shape has partly changed into a wavy shape. As described above, the tomographic image of an eye portion obtained using the OCT is a three-dimensional image. However, to simplify the following description, FIGS. 20A to 20C illustrate two-dimensional images that can be obtained by cutting the three-dimensional image along a plane. Further, since the retinal pigment epithelium is a thin layer, it is indicated by a single line in FIGS. 20A to 20C.
In the following description, a boundary between the retinal pigment epithelium and its upper or lower layer is referred to as a “boundary of the retinal pigment epithelium”, or is simply referred to as a “layer boundary.” Further, an estimated boundary position that represents a layer boundary in a normal state (i.e., in a non-diseased state) is referred to as a “normal structure of the boundary of the retinal pigment epithelium”, or is simply referred to as a “normal structure.” Further, an example of the age-related macular degeneration diagnosing method using the OCT includes obtaining an actual boundary (indicated by 1401 in FIG. 20C) of the retinal pigment epithelium based on the image illustrated in FIG. 20B, as a boundary actually observable on the tomographic image, and further obtaining its normal structure (indicated by 1402 in FIG. 20C) on the same tomographic image. The diagnosing method further includes quantifying the state of the disease according to an area (or a volume) that represents a difference (a hatched portion illustrated in FIG. 20C) between the actual boundary (1401) of the retinal pigment epithelium that is observable on the tomographic image and its normal structure (1402) on the same tomographic image.
However, the above-described work is conventionally performed based on a manual work by a physician or an engineer. It is therefore desired to reduce the operator's burden and eliminate the resulting dispersion. In this respect, it is expected to automatically detect the boundary of the retinal pigment epithelium from the tomographic image and estimate its normal structure.
The above-described detection of the boundary of the retinal pigment epithelium can be performed using a technique discussed in Japanese Patent Application Laid-Open No. 2008-73099 or in Japanese Patent Application Laid-Open No. 2007-325831. On the other hand, because the above-described normal structure cannot be observed as image features on the tomographic image, the normal structure cannot be estimated using the technique discussed in Japanese Patent Application Laid-Open No. 2008-73099 or in Japanese Patent Application Laid-Open No. 2007-325831. Hence, it is usual that an elliptic curve applied to a boundary of the retinal pigment epithelium detected from a two-dimensional tomographic image (i.e., B-scan image) so as to minimize square errors is regarded as its normal structure.
FIGS. 21A to 21D are schematic views illustrating examples of a layer structure of an eye portion that has been captured using the OCT.
More specifically, the layer structures illustrated in FIGS. 21A to 21D are examples including a macula lutea portion of the retina. In general, the tomographic image of an eye portion obtained using the OCT is a three-dimensional image. However, to simplify the following description, FIGS. 21A to 21D illustrate two-dimensional images that can be obtained by cutting the three-dimensional image along a plane.
As illustrated in FIGS. 21A to 21D, a retinal pigment epithelium 1001, a nerve fiber layer 1002, and an inner limiting membrane 1003 can be observed as individually discriminable layers. For example, in a case where a tomographic image illustrated in FIG. 21A is input, the stage of a disease (e.g., glaucoma) or the degree of recovery from the disease after treatment can be quantitatively diagnosed by measuring a thickness (indicated by T1 in FIG. 21A) of the nerve fiber layer 1002 or a thickness (indicated by T2 in FIG. 21A) of the entire retinal layer.
To measure the thickness of each layer, it was conventionally necessary for a physician or an engineer to manually designate a boundary of each layer of the retina on a two-dimensional tomographic image (i.e., a B-scan image), which can be obtained by clipping a target cross section from a three-dimensionally captured tomographic image. For example, to check the thickness (T1) of the nerve fiber layer 1002 illustrated in FIG. 21A, it was necessary to designate the inner limiting membrane 1003 and a lower boundary 1004 of the nerve fiber layer (i.e., a boundary between the nerve fiber layer 1002 and a layer positioned beneath the nerve fiber layer 1002) on the tomographic image, as understood from FIG. 21B. Further, to check the thickness (indicated by T2 in FIG. 21A) of the entire retinal layer, it was further necessary to designate a boundary 1005 of the retinal pigment epithelium 1001 (i.e., a boundary between the retinal pigment epithelium 1001 and a layer positioned beneath the retinal pigment epithelium 1001).
Further, to obtain a three-dimensional distribution with respect to the thickness of each layer, it was necessary to designate a boundary of a target layer on each two-dimensional tomographic image based on the assumption that a three-dimensional tomographic image is an assembly of a plurality of two-dimensional tomographic images.
However, the work for manually designating a layer boundary is not easy for an operator (e.g., a physician or an engineer). Further, the work for manually designating the boundary of the target layer tends to generate a dispersion that results from differences of individual operators as well as differences in work date and time. Therefore, performing quantification at an expected accuracy level was difficult.
As discussed in Japanese Patent Application Laid-Open No. 2008-73099 and Japanese Patent Application Laid-Open No. 2007-325831, for the purpose of reducing the operator's burden and eliminating the dispersion in the work, there is a conventional technique for causing a computer to detect a boundary of each layer of the retina from a tomographic image and measuring the thickness of each layer.
Further, the age-related macular degeneration or a similar disease is characteristic in that the shape of the retinal pigment epithelium changes into a wavy shape according to the condition of a disease. Therefore, it is effective to quantify the degree of its deformation to identify the condition of the disease.
FIG. 21A illustrates an example of a retinal layer structure of a normal eye. FIG. 21C illustrates an example of a retinal layer structure that has changed due to the age-related macular degeneration. A retinal pigment epithelium 1001 of the normal eye illustrated in FIG. 21A includes a smooth curve that represents a boundary structure. On the other hand, a retinal pigment epithelium 1001 having been modified by the age-related macular degeneration illustrated in FIG. 21C has a portion whose shape has partly changed into a wavy shape.
In the following description, an estimated boundary position that represents a layer boundary in a normal state (i.e., in a non-diseased state) is referred to as a “normal structure of the boundary of the retinal pigment epithelium”, or is simply referred to as a “normal structure.” Further, an example of the age-related macular degeneration diagnosing method using the OCT includes obtaining an actual boundary (actual measurement data indicated by a solid line 1005 in FIG. 20D) of the retinal pigment epithelium, as a boundary actually observable on the tomographic image, and further obtaining its normal structure (estimation data indicated by a dotted line 1006 in FIG. 21D) on the same tomographic image. The diagnosing method further includes quantifying the state of the disease according to an area (or an overall volume) in each cross section that represents a difference (a hatched portion illustrated in FIG. 21D) between the actual boundary (1005) of the retinal pigment epithelium that is observable on the tomographic image and its normal structure (1006) on the same tomographic image.
However, the above-described work is conventionally performed based on a manual work by a physician or an engineer. It is therefore desired to reduce the operator's burden and eliminate the resulting dispersion. In this respect, it is expected to automatically detect the boundary of the retinal pigment epithelium from the tomographic image and estimate its normal structure.
The above-described detection of the boundary of the retinal pigment epithelium can be performed using the technique discussed in Japanese Patent Application Laid-Open No. 2008-73099 or in Japanese Patent Application Laid-Open No. 2007-325831. On the other hand, because the above-described normal structure cannot be observed as image features on the tomographic image, the normal structure cannot be estimated using the technique discussed in the above-described patent literatures. Hence, it is usual that an elliptic curve applied to a boundary of the retinal pigment epithelium detected from a two-dimensional tomographic image (i.e., B-scan image) so as to minimize square errors is regarded as its normal structure.
The retinal pigment epithelium 1001 is a very thin layer. Therefore, in general, the boundary 1005 of the retinal pigment epithelium may be referred to as “retinal pigment epithelium itself.” Therefore, in the following description, the “boundary of the retinal pigment epithelium” can be regarded as being equivalent to the “retinal pigment epithelium itself.” Similarly, the “normal structure of the boundary of the retinal pigment epithelium” can be regarded as being equivalent to the “normal structure of the retinal pigment epithelium itself.”
However, the above-described normal structure having been estimated by applying an elliptic curve according to the conventional least squares method tends to be greatly different from the actual normal structure. Therefore, even if an area is obtainable as a difference between the normal structure and a detected layer boundary, the obtained area cannot be used as a reliable index that can quantify the state of a disease. Further, if a blood vessel or a facula is included in the tomographic image, the boundary 1005 of the retinal pigment epithelium may not be clearly observed at a portion where the boundary 1005 is overlapped with the blood vessel or the facula. Namely, acquiring the image features of the boundary 1005 of the retinal pigment epithelium may partly fail due to the influence of such an obstacle.